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Most companies have a large number of projects that they would like to do for various reasons. However, usually there is never enough time and money available to complete all of them. Selecting a portfolio from available project proposals is crucial for the success of each company. This paper proposes a practical framework for modelling projects portfolio selection problem with fuzzy parameters resulting...
Experts are able to predict sales based on approximate reasoning and subjective beliefs related to market trends in general but also to imprecise linguistic concepts about time series evolution. Linguistic concepts are linked with demand and supply, but their dependencies are difficult to be captured via traditional methods for crisp data analysis. There are data mining techniques that provide linguistic...
The work presented in this paper concerns discourse structure analysis and its applications to intra- and inter-document search. In a typical application, which could be called “rhetorical browsing”, the system will provide assistance to a journal reader in order to focus on texts and passages presenting certain kind of information and comments, according to his/her current interest: may be raw information,...
The quality measures for bipolar linguistic summaries of data, as proposed in our previous work [1], are further developed. The summaries introduced in [2] are assumed to be an extension of the “classical” linguistic summarization (cf. [3], [4]), a human-consistent data mining technique revealing complex patterns present in data. This extension consists in using the “and possibly” to build a summary...
In this paper we present an intelligent consensus reaching support system within the group of individuals under fuzzy preferences and fuzzy majority. Our solution is based on the idea of soft degree of consensus proposed by Fedrizzi, Kacprzyk, Nurmi and Zadrozny, which is meant as the statement: “most of the individuals agree with the most of the options”. Our new comprehensive model provides an effective...
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